Datasets:
Tasks:
Translation
Multilinguality:
multilingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
License:
# coding=utf-8 | |
# Copyright 2020 HuggingFace Datasets Authors. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# Lint as: python3 | |
import os | |
import datasets | |
_DESCRIPTION = """\ | |
The QCRI Educational Domain Corpus (formerly QCRI AMARA Corpus) is an open multilingual collection of subtitles for educational videos and lectures collaboratively transcribed and translated over the AMARA web-based platform. | |
Developed by: Qatar Computing Research Institute, Arabic Language Technologies Group | |
The QED Corpus is made public for RESEARCH purpose only. | |
The corpus is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Copyright Qatar Computing Research Institute. All rights reserved. | |
225 languages, 9,291 bitexts | |
total number of files: 271,558 | |
total number of tokens: 371.76M | |
total number of sentence fragments: 30.93M | |
""" | |
_HOMEPAGE_URL = "http://opus.nlpl.eu/QED.php" | |
_CITATION = """\ | |
A. Abdelali, F. Guzman, H. Sajjad and S. Vogel, "The AMARA Corpus: Building parallel language resources for the educational domain", The Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC'14). Reykjavik, Iceland, 2014. Pp. 1856-1862. Isbn. 978-2-9517408-8-4. | |
""" | |
_VERSION = "2.0.0" | |
_BASE_NAME = "QED.{}.{}" | |
_BASE_URL = "https://object.pouta.csc.fi/OPUS-QED/v2.0a/moses/{}-{}.txt.zip" | |
# Please note that only few pairs are shown here. You can use config to generate data for all language pairs | |
_LANGUAGE_PAIRS = [ | |
("ar", "ko"), | |
("de", "fr"), | |
("es", "it"), | |
("en", "ja"), | |
("he", "nl"), | |
] | |
class QEDAmaraConfig(datasets.BuilderConfig): | |
def __init__(self, *args, lang1=None, lang2=None, **kwargs): | |
super().__init__( | |
*args, | |
name=f"{lang1}-{lang2}", | |
**kwargs, | |
) | |
self.lang1 = lang1 | |
self.lang2 = lang2 | |
class QEDAmara(datasets.GeneratorBasedBuilder): | |
BUILDER_CONFIGS = [ | |
QEDAmaraConfig( | |
lang1=lang1, | |
lang2=lang2, | |
description=f"Translating {lang1} to {lang2} or vice versa", | |
version=datasets.Version(_VERSION), | |
) | |
for lang1, lang2 in _LANGUAGE_PAIRS | |
] | |
BUILDER_CONFIG_CLASS = QEDAmaraConfig | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)), | |
}, | |
), | |
supervised_keys=None, | |
homepage=_HOMEPAGE_URL, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
def _base_url(lang1, lang2): | |
return _BASE_URL.format(lang1, lang2) | |
download_url = _base_url(self.config.lang1, self.config.lang2) | |
path = dl_manager.download_and_extract(download_url) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"datapath": path}, | |
) | |
] | |
def _generate_examples(self, datapath): | |
l1, l2 = self.config.lang1, self.config.lang2 | |
folder = l1 + "-" + l2 | |
l1_file = _BASE_NAME.format(folder, l1) | |
l2_file = _BASE_NAME.format(folder, l2) | |
l1_path = os.path.join(datapath, l1_file) | |
l2_path = os.path.join(datapath, l2_file) | |
with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2: | |
for sentence_counter, (x, y) in enumerate(zip(f1, f2)): | |
x = x.strip() | |
y = y.strip() | |
result = ( | |
sentence_counter, | |
{ | |
"id": str(sentence_counter), | |
"translation": {l1: x, l2: y}, | |
}, | |
) | |
sentence_counter += 1 | |
yield result | |